Paper Info
Title
H-Matrix - Hierarchical Matrix for Visual Analysis of Cross-Linguistic Features in Large Learner Corpora.
Abstract
This paper presents a visualization technique for cross-linguistic error analysis in large learner corpora. H-Matrix combines a matrix, which is commonly used by linguists to investigate cross-linguistic patterns, with a tree diagram to aggregate and interactively re-weight the importance of matrix rows to create custom investigative views. Our technique can help experts to perform data operations, such as, feature aggregation, filtering, ordering and language comparison interactively without having to reprocess the data. H-Matrix dynamically links the high-level multi-language overview to the extracted textual examples, and a reading view where linguists can see the detected features in context, confirm and generate hypotheses.
Year
DOI
Venue
2019
10.1109/VISUAL.2019.8933537
VIS
Keywords
Field
DocType
Feature extraction,Linguistics,Data visualization,Visualization,Task analysis,Heating systems,Tools
Row,Tree diagram,Computer science,Visualization,Learner corpora,Matrix (mathematics),H matrix,Hierarchical matrix,Filter (signal processing),Theoretical computer science,Artificial intelligence,Natural language processing
Conference
ISBN
Citations 
PageRank 
978-1-7281-4941-7
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Mariana Shimabukuro100.34
Jessica Zipf200.34
Mennatallah El-Assady312013.73
Christopher Collins4103749.74